Customer records and other information that are often a part of complex data systems and business applications present a variety of challenges in management, identification, analysis and segregation, for example. Information often exists in multiple locations within an organization, within an enterprise, or even more globally across enterprises. Furthermore, information is often represented in an optimal way for local applications, and, usually, not all applications within the organization, enterprise, or globally across enterprises require, use, or are allowed to access all of the information that exists. As a result, the amount of unstructured data that may reside in planned and developing databases could easily become out of hand, causing storage and processing inefficiencies. With such an amount of unstructured data, additional complexities arise, especially when the data is present on different platforms, is of varying freshness, and may be inconsistent or duplicative across the platforms.
Within a complex data system, where there exists multiple databases each having records comprising particular data, determining duplicate or related records can be particularly difficult. Quality issues also arise in which data stewardship matters become a central concern. Further, in customer relationship management (CRM) matters, which often necessitate data integrity to realize optimal returns on data structure investments, removing “bad customer data” and especially duplicate customer data is of key concern.